The State of
HaaS
Insights on the Trends and Key Metrics
Driving Hardware-as-a-Service
2022
Report by Silicon Valley Bank with
support from Eclipse Ventures
THE STATE OF HAAS 2
Macro:
Trends Driving HaaS
4
Investment:
Deals, Dollars and Valuations
9
11
The State of HaaS
7Rise of HaaS:
A New Model for Hardware Startups
Metrics that Matter:
The Key Performance Indicators
for Evaluating HaaS Companies
THE STATE OF HAAS 3
Executive Summary
Hardware companies are evolving their approach. At SVB, we’ve witnessed the emergence of
Hardware-as-a-Service (HaaS), a model that companies use to provide hardware, software,
maintenance and other services in one package for a monthly (recurring) fee. We issued our first
custom HaaS loan in 2017.
Digital transformation is raising the expectations of what hardware-enabled industries expect from
technology. Hardware, like an industrial robot, is now just part of the overall offering, providing
a platform for additional services, like real-time monitoring, predictive diagnostics and AI-powered
analytics. HaaS companies are rising to meet these challenges with a business model more suited
to their customers. Instead of significant upfront capital expenditures, the HaaS model transforms
this into a recurring payment more easily accommodated as an operating expense. For the HaaS
company, this provides more predictable revenue and more sticky customer relationships.
The recurring revenue model is spreading to every sector of frontier technology, from construction
robots mapping out job sites and security bots roaming office buildings to autonomous drones
gathering data from the open ocean. HaaS companies are creating additional value by using their
physical assets to build large data sets and create additional services. By bringing a greater depth
and breadth of insights to their customers, HaaS companies are increasing customer lifetime value,
ultimately driving higher profits.
We wanted to better understand how HaaS companies are performing. In the first half of this
report we dive into the key trends driving the adoption and financing of the HaaS model. For the
second half of this report, we surveyed 400 top clients in our proprietary State of HaaS Survey. We
partnered with Eclipse Ventures, a venture firm that partners with exceptional companies that
make physical industries more efficient, resilient, and profitable, to determine the key performance
metrics for HaaS companies. Since inception in 2015, the Eclipse Team has focused on
transforming physical industries. They helped us identify the six metrics that matter (for HaaS
companies) and partnered with us to provide the aggregated results from our survey.
Matthew Trotter
Senior Market Manager,
SVB Frontier Tech and Climate Tech Practice
4
Macro:
Trends Driving HaaS
THE STATE OF HAAS 4
Fifty-three years ago one of the world’s first smart
devices rocketed into outer space. The Apollo Guidance
Computer weighed 70 pounds and cost $200k.1Its 32k
bits of RAM got the astronauts to the moon and back, but
it wouldn’t have been enough memory to store the
content from a single page of this report. Computers
have evolved. Today the iPhone is one million times more
powerful than the Apollo computer and at a tiny fraction
of the size and price. Great leaps in processing power
and efficiency have made it feasible to fit a computer
into nearly everything. It’s not just phones that are
getting smart. More than 131 million households own a
smart speaker, 78 million own a smart security camera,
and electronics now comprise 40% of a new vehicle’s
total cost.
On the factory floor, in warehouses and in fields, robots
automate tedious and dangerous work, while sensors
gather the data that businesses crave. The barrier for
hardware innovation is lower than ever. Parts that were
once custom built are now available off the shelf (OTS).
The minimum viable computer costs less than $20.
Hobbyists and engineers can grab a Raspberry Pi and
equip a circuit board to just about anything.
Spurred on by digital adoption, the pace of innovation
in the hardware space has accelerated in recent years.
If it has a battery, it probably has a WiFi connection.
Yet hardware companies now face new challenges.
Computers are becoming a commodity. Input costs are
halving every year, forcing companies to differentiate
in other ways, such as their business model. Startups
are creating robots that are easier to integrate and
at the same time finding new revenue streams from
the data they mine. Hardware is breaking out from
its conventional realm and proliferating across new
and exciting applications.
Faster, Smaller,
Cheaper Bots
Notes: 1) Equivalent to $1.6M today. 2) Average CPI per year, indexed to 100 for 2005. 3) Compound Annual Growth Rate (CAGR)
reflects projected change from 2022 to 2027. 4) Internal Combustion Engine (ICE) vehicles. The chip count in 2000 is an
estimated equivalent of $150 of chips. 5) Robots per 10,000 workers in 2020, latest available data. 6) Application of new rob ots
Source: Computer-History.com, US Bureau of Labor Statistics, Capital IQ, Statista, Deloitte, Wikipedia Transistor Count,
International Federation of Robotics, and SVB analysis. THE STATE OF HAAS 5
Computer Prices2and Computer
Processing Power Over Time
Global Households with Smart Devices3
Electronics’ Percentage of New Car4Costs Robot Density by Country5and Global Robot
Installations by Industrial Application6
100
48
28
7M
14M
30M
80M
2005 2007 2009 2011 2013 2015 2017 2019 2021
Prices fell 72%
since 2005.
131M
78M
73M
72M
48M
335M
181M
178M
172M
116M
Speakers
Security Cameras
Big Appliances
Small Appliances
Smoke Detectors
21%
18%
19%
19%
19%
2022 Projected CAGR
2027 forecast
932
605
390
371
289
255
246
246
224
South Korea
Singapore
Japan
Germany
Sweden
Hong Kong
United States
China
Denmark
18%
27%
40% 45%
2000 2010 2020 2030
Handling
43%
Welding
17%
Assembling
12%
Cleanroom
9%
Dispensing
2%
Processing
1%
Other
16%
CPI: Computers, Peripherals, and Smart Devices
Average number of transistors on a microchip
Processing
power doubles
every 1-2 years.
Actual Projected
In 2000, the average ICE
vehicle had fewer than
30 semiconductor chips.
In 2022, most ICE vehicles
have around100-150 chips.
Electric vehicles can have
up to 3,000
$8.5M
$3.0M
$3.0M
The traditional “transactional” sales model for hardware
companies is fading, with a new “recurring” model —
Hardware-as-a-Service (HaaS) —taking over. The HaaS
sales model is sweeping across all hardware industries,
from home gym equipment to factory robots. It allows
companies to have a more predictable revenue stream
and build deeper relationships that go beyond the initial
sale to include services such as automation, monitoring
and analytics. The payoff for vendors is a higher lifetime
value per customer, provided by incremental revenue
from these value-added services and greater stickiness
of the relationship.
We identified and analyzed a cohort of nearly 600
frontier tech companies with subscription- and usage-
based sales models. Compared to traditional hardware
companies, which rely on one-time sales, the formation
rates of HaaS companies rocketed from 2015, increasing
150% by 2017, and maintained a higher rate of
formations than traditional (and SaaS) companies. HaaS
companies were highly concentrated in both California
and Massachusetts (thanks in large part to MIT), two
hotbeds for robotics and transportation tech.
Increasingly, HaaS companies are repositioning to solve
data problems. The focus on analytics and monitoring
solutions, instead of the enabling hardware, is pushing
engineers to create machines more oriented to that
purpose. OTS parts and interchangeable components are
lowering the barrier of entry to build robots.
Entrepreneurs who might have shied away from building
hardware a decade ago are now diving in, as evidenced
by a surge in venture capital (VC) deals since 2018. They
can take confidence from the interest investors are
showing in the HaaS model, with deal sizes trending
higher in comparison to both traditional hardware and
SaaS deals.
Out with the Old,
in with the HaaS
Notes:1) Total companies closing a first VC round. Indexed to 2015. HaaS companies are hardware companies with a recurring sales model. Traditional
hardware companies have a one-time sales model. SaaS are enterprise software companies. 2) VC deals since 2015. 3) US-based companies.
Source: PitchBook and SVB analysis. THE STATE OF HAAS 6
Rate of US Company Formation by
Sales Model1
Geographic Distribution of US VC
Deals2by Sales Model
58%
5%
13%
3%
4%
3%
14%
HaaS
companies
cluster near
robotics hubs
like Silicon
Valley and
Boston.
39%
13%
6%
5%
4%
3%
30%
California
New York
Massachusetts
Texas
Washington
Colorado
Other
HaaS SaaS
0
50
100
150
200
250
300
2015 2016 2017 2018 2019 2020 2021
Formation Rate (Index = 100)
$0M
$100M
$200M
$300M
$400M
$500M
$600M
$700M
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
HaaS formations surge
HaaS deals
bubble up, led
by aerospace.
Robotics
Agriculture
Sensors/Cameras
Industrial IoT
Aerospace
Manufacturing
Transportation Pre-Money Valuation
First VC Round Deal Size3by
Sales Model
VC Deal Sizes for US HaaS
Companies by Sector
HaaS Traditional Hardware
Enterprise
software spreads
beyond traditional
tech hubs.
Middle 50% of Companies Median
7
Rise of HaaS:
A New Model Emerges for
Hardware Startups
THE STATE OF HAAS 7
For the traditional hardware sales model, revenue is
recognized only once –at the time of purchase. A new
order comes in, inventory is checked, the product is
shipped, and within 95 days payment is received. That’s
fine initially to gain market traction, but companies
pay for it in the long run with high customer acquisition
costs and unpredictable revenue swings. Conversely,
a subscription sales model is more scalable, predictable
and profitable. Software companies figured this out in the
early 2000s, starting with Salesforce in 1999 launching
their CRM product as a Software-as-a-Service (SaaS)
solution. The result: higher profitability and stickier
customer relationships.
It was Amazon that first applied the as-a-service (aaS)
model to hardware. When Amazon Web Services (AWS)
launched in 2006, the only way for companies to operate
their data network infrastructure was to buy the
equipment (servers), lease a place to put it and hire
people to run it. Cloud computing —the original HaaS
model use case —was a win-win for customers and
providers alike. Clients avoided the expense of setting up
costly infrastructure and valued the flexibility of usage-
based rates. Amazon proved that after an initial payback
period HaaS can be a highly scalable way to grow revenue.
The growth trajectory for AWS’s operating income (similar
to other SaaS models) starts low and builds as customer
contracts start to layer and reach profitability. Compared
to Amazon’s razor thin e-commerce margins (1.6% in
2021), AWS is highly profitable (29.8% in 2021).
To measure success, HaaS companies are embracing a
new set of key metrics that combine elements from both
SaaS and traditional hardware approaches. Among these
metrics, payback period and customer lifetime value are
key. Later in this report we’ll identify the six key
benchmarks every HaaS company should know.
A Better Model
for Hardware
Notes: 1) HaaS includes hardware companies with an aaS business model. Traditional hardware companies do one-
time sales only. 2) Operating income is annual sales minus annual expenses.
Source: Amazon Annual Reports and SVB analysis. THE STATE OF HAAS 8
0 3 6 9 12 15 18 21 24 27 30 33 36
Cumulative Cash Flow
-$5B
$0B
$5B
$10B
$15B
$20B
2013 2014 2015 2016 2017 2018 2019 2020 2021
Cash Flow by Business Model: HaaS vs. Traditional Hardware1
Key Metrics by Business Model Case Study: Amazon’s Operating Income2
0 1 2 3 12 18
Total cash
received 95 days
from order
Longer payback period, cash locked in assets
Higher earning potential per
customer, from multi-year contracts
and value-added services
Unpredictable cash flow as
revenue relies on new sales
Lower customer
acquisition cost
In 2021, AWS accounted
for 76% of Amazon’s
operating income.
Incremental Sale Period
Months Since Order Months Since Order
One
-time Sales
Bill of
Materials (BOM)
Cost
Deployment Cost
Inventory
Lead Times
Hardware SaaS HaaS
New Contracts
Payback Period
Customer
Acquisition Cost
(CAC)
Churn
Customer Lifetime
Value (CLV)
Committed Monthly
Recurring Revenue
New Contracts
Payback Period
CAC
CLV
BOM Cost
Deployment Cost
Inventory
Lead Times
+ = AWS Amazon (all other segments)
HaaS Traditional Hardware
Payback
Deployment
Cost
BOM
Cost
Revenue Stops
9
Investment:
Deals, Dollars and Valuations
THE STATE OF HAAS 9
$2.8B $3.4B $3.7B $5.5B $10.4B $2.9B
256 274 253 260 289
246
2017 2018 2019 2020 2021 2022
$0B
$3B
$6B
$9B
Jan-21 May-21 Sep-21 Jan-22 May-22
Hardware investors favor a recurring revenue sales
model. In 2021, total US VC investment in HaaS
companies reached $10.4B, an 89% year-over-year
(YoY) increase. Of this, $2.2B of investment went to
early-stage HaaS companies. The median deal size for
a HaaS seed round was $6.8M in 2022, a jump of 51%
from 2021, and more than double the $3.0M raised by
traditional hardware companies. For reference, the
median seed deal for SaaS companies in 2021 was
$2.6M. However, recent macroeconomic headwinds are
hampering activity, with the total number of HaaS deals
in 2022 down 18% over the same period last year. As the
market enters into what could be a sustained downturn,
HaaS companies may turn to alternative financing types,
such as debt, to extend their runways instead of raising
equity on unfavorable terms.
For growth companies, metrics don’t completely
justify the market opportunity, which in many cases is
being established by said companies. For example, there
is no current market for flying taxis, but in theory the
technology could disrupt many traditional industries.
This dynamic poses a challenge for investors, especially
those without serious industry expertise, and often
results in a financing chasm –between the MVP and
commercialization –for hardware founders to cross.
Our analysis found that it takes at least $4 of capital
to generate $1 of revenue for HaaS companies that have
reached the $10M revenue threshold. The capital-
intensive nature of most hardware solutions combined
with the difficulty raising growth financing has led
hardware founders to consider unconventional strategies.
For example, of the seven HaaS companies that have
gone public since January 2021, all but one chose to exit
via a special purpose acquisition company (SPAC). Even
the one IPO, Knightscope, had been one of the first to try
equity crowdfunding.
Investors Buy into
the Concept
Notes: 1) HaaS deals include hardware companies with aaS business models. Deals as of
6/13/2022. Projections based on year to date (YTD) pace. 2) US VC investment. 3) Revenue is ARR.
Source: PitchBook and SVB analysis.
US VC Investment in HaaS Companies1HaaS Deal Size2by Series
Equity Capital Raised by Revenue
Band for US HaaS Companies3
Notable HaaS Exits Since January 2021
$3M $8M $17M $26M $50M
$76M $126M
$225M
$0
$1-$99K
$100K-
$999K
$1M-
$4.9M
$5M-
$9.9M
$10M-
$24.9M
$25M-
$49.9M
$50M-
$75M
Revenue Bands
11%
12%
19%
24%
34%
Industrials
Aerospace
Transportation
Hardware Infrastructure
Other
2021 VC
By Sector
$6.7B
SPAC IPO
Middle 50% of Companies Median
$M
$2M
$4M
$6M
$8M
$10M
2019
2020
2021
2022
Seed
$M
$5M
$10M
$15M
$20M
$25M
$30M
$35M
$40M
2019
2020
2021
2022
Series A
$M
$10M
$20M
$30M
$40M
$50M
$60M
$70M
$80M
2019
2020
2021
2022
Series B
Capital Invested
Number of Deals
Projected Invested Capital
Projected Deals YTD Deals
HaaS Exits - Value at Exit
THE STATE OF HAAS 10
Median Capital Raised Middle 50% of Companies
Company
Exit
Date
Revenue
Multiple at Exit
Years from
Round 1 to Exit
ChargePoint
Feb-21
16x
12.1
TuSimple Holdings
Apr-21
NMF
5.6
Evolv
Technology Jul-21
142x
7.9
Spire Global
Aug-21
37x
9.1
Joby Aviation
Aug-21 Pre-
Revenue
7.7
Planet Labs
Dec-21
21x
8.5
Knightscope
Jan-22
53x
8.8
11
Metrics
that Matter:
The Key Performance Metrics for
Evaluating HaaS Companies
THE STATE OF HAAS 11
Relevant, informative, actionable metrics are critical
for companies to benchmark their performance and
for investors to appropriately evaluate them. That’s
especially true at the growth stage, where startups must
meet major milestones, typically tied to a combination
of metrics. To better understand what differentiates
success, we asked our partners at Eclipse Ventures
to help identify the metrics that should matter most
to a HaaS company. A cohort of HaaS companies
spanning all life stages and sectors were then surveyed.
The results —presented on the following pages —
offer a guide.
Here’s a breakdown of the metrics that matter
and our takeaway for each:
1. Machine Lifetime Value (MLV) to BOM Ratio: Aim for
a 7x return on your machine’s lifetime value to BOM.
2. Customer Contract to BOM Ratio: Structure
contracts to reach the payback BOM cost.
3. Operating Profit Margin: Machine operating costs
need to be manageable. Companies should strive for
around 15% of revenue. If you’re not there now,
improve this number over time.
4. Lead Time Efficiency Ratio: Circumvent supply chain
disruption by maintaining up-to-date lead times
and sufficient inventory on hand for critical parts.
5. Machine Acquisition Cost (MAC) Multiple: Avoid
bloat by making sure your MAC multiple stays
low as you grow your business.
6. Machine Churn: Keep machine churn low to maintain
high CLV and confidence.
How to Evaluate HaaS
Performance
Notes: 1) We identified these key metrics based on our proprietary survey of HaaS companies. When the results indicated a clear benchmark, we provided
it. 2) OPEX is the cost to operate a HaaS system per year. 3) Operating profit margin is a static machine’s annual revenue minus its operating expenses.
Source: SVB State of HaaS Survey results and SVB analysis.
The Six Metrics that Matter for HaaS Companies1
THE STATE OF HAAS 12
Annual Revenue − Annual OPEX ∗ Expected Service Life
BOMCosts
Annual Revenue − Annual OPEX ∗ Years in Contract
BOM Costs
Cost of Sales + Cost of Implementation
New Machines Deployed
LTV
# Machines Extracted from Deployment in Period
# New Machines Deployed in Period
Customer
Contract to
BOM Cost
Lead Time
Efficiency Ratio
Operating
Margin Growth
Rate
Machine
Acquisition Cost
(MAC) Multiple
Machine Lifetime
Value (MLV) to BOM
Ratio2
Machine Churn
Are you getting enough ROI per unit?
The median lifetime value of the HaaS
survey cohort was 7x BOM costs.
Is the contract long enough?
At a minimum, contracts should
exceed their payback period.
How efficient is your system?
Higher efficiency generally leads to
higher profits. The target operating
profit margin is 85%.3
Will you stay supplied?
Longer lead times require more
inventory to be held. Balance the
cost of holding inventory vs. lost
revenue opportunities.
Are you selling efficiently?
A higher MAC multiple could mean
inefficient sales and/or
implementation efforts. This metric
should trend down over time.
Is your system reliable and valued?
Lower machine churn results in a
higher customer lifetime value.
365
(Avg.Lead Time + (Longest Lead Time ∗ % of BOM for Longest Lead Time)
Monthly OPEX Start Period
MonthlyRev Start Period −Monthly OPEX End Period
Monthly Rev End Period
Monthly OPEX Start Period
Monthly Rev Start Period
Typically, most HaaS startup customers start out under
a pilot contract. These pilots are a valuable way for
startups and customers to prove out the technology
and test drive the solution at a scale and cost that
isn’t excessive to either party. Our survey found that
the median pilot contract lasts three months, and 72%
ultimately convert to a production contract.
HaaS investors prefer pilot contracts to have an
auto-conversion clause. The clause provides a higher
probability of attaining a longer-term, larger (production)
contract without the need for excessive negotiations or
down time (providing the system meets the milestones
for auto-conversion) . We found 35% of HaaS companies
use contracts with an auto-conversion clause.
Typically, HaaS companies create additional value from
the data they are collecting. Among respondents, 41%
said they own the data generated by their hardware.
Another 16% indicated that they either have a data-
sharing agreement or some other kind of understanding
with their clients.
One benefit to the HaaS model is converting large capital
expenditures, which typically require financial planning
and senior management sign-off, to periodic “operating”
expenses. This generally means a shorter sales period,
lower selling expense and simpler account management.
Customer Contracts
Breakdown
Notes: 1) Results come from a survey of US HaaS companies identified by SVB. HaaS includes hardware companies with a recurrin g
revenue business model. 2) Stages based on HaaS revenue: pilot companies have less than $100K, production companies have $100K-
$1M, scaled companies have over $1M. Average HaaS revenue for scaled companies is $41M.
Source: SVB State of HaaS Survey results and SVB analysis. THE STATE OF HAAS 13
HaaS Contract Types by Revenue1Length of Pilot Contracts by Revenue2
HaaS Company Cohort Revenue Breakdown HaaS Company Cohort Data Agreement
Breakdown
88%
38%
26%
11%
63%
72%
Sub-$100K $100K-$1M $1M+
Revenue Bands
105
90
90
183
117
150
0
45
90
135
180
225
270
315
360
Pilot Production Scaled
Days
HaaS Revenue Stage
of pilot contracts
auto-convert
to production
contracts based on
milestones.
45%
30%
15%
10%
Total Revenue
Recurring
Payments
One-Time Sales
Non-Recurring
Engineering (NRE)
Other
67%
33%
Recurring Revenue
Subscription-
Based
Usage-Based
16%
23%
20%
41%
Data Agreements
HaaS Customer
Owns Data
Other
HaaS Provider
Owns Data
35%
Pilot Production Other Middle 50% Companies Median Average
Data Ownership
Not Addressed
in Contract
HaaS Companies
There are two common problems that stifle promising
HaaS companies: machine performance and customer
expectations. The pilot stage of a contract gives
companies the opportunity to refine their offerings to
better meet customer needs on a manageable scale
without major cost outlays. Managing cash (flows) is
probably the main drawback of the HaaS model, as
vendors have to outlay the full cost of a system but
not recoup those costs for months or even years. Unlike
traditional hardware sales, in which customers pay back
the cost of the hardware plus profit within 95 days,
HaaS customers spread that payment over the life of a
subscription term. We found the median payback period
was around 16 months across all HaaS life stages and
sectors. The top quartile of systems recouped costs in
10 months, while the bottom quartile took 32 months to
break even. However, it is reasonable for the payback
period to vary based on the scale and service life of the
system. For example, a satellite might cost $1M to build
and take three years to payback, but if its service
life is 15 years, it’s well worth the wait.
On the conversion side, HaaS companies should monitor
the percent of machines being returned from deployment
in a given period. Reliability is key. Customer churn rates
for HaaS companies should be better than the rates for
their enterprise software peers, as hardware integrations
inherently have higher switching costs. According to
Bessemer Venture Partners, the annual customer churn
rate for top enterprise software companies is between
5%-7% a year. HaaS systems tend to replace or
supplement human labor costs, and their lack of downtime
is a major benefit for customers. Keeping machines
operating is more important for the HaaS model than
it is for the traditional hardware model, especially if the
contract is usage-based. Profitability depends on
maximizing service life.
Machine
Value Analysis
THE STATE OF HAAS 14
Time (in Months) to Generate First Revenue
3.0
3.6
0
1
2
3
4
5
HaaS Companies
Months from Deployment
The median period
from executed
contract to first
revenue is
3 months.
Payback Period per HaaS System1
Middle 50% Companies Median Average
Expected Machine Service Life2
5.0
8.0
7.0
6.9
7.5
7.1
0
2
4
6
8
10
12
Pilot Production Scaled
Years
HaaS Revenue Stage
Middle 50% Companies Median
Payback Period as a Percent of Expected
Machine Service Life
25%
0%
5%
10%
15%
20%
25%
30%
35%
40%
HaaS Companies
Payback period
accounts for
one-quarter
of a HaaS
system’s
service life.
Middle 50% Companies Median
Notes: 1) The payback period is the time it takes monthly revenue minus expenses to equal BOM costs. 2) Stages based on HaaS revenue: pilot companies
have less than $100K, production companies have $100K-$1M, scaled companies have over $1M. Average HaaS revenue for scaled companies is $41M.
Source: SVB State of HaaS Survey results and SVB analysis.
Average
-3x
x
3x
6x
012 24 36
Cumulative Cash Flow
The median
payback period:
16 months
2x ROI:
32 months
Top quartile
payback:
10 months
Middle 50% Companies Median
Bottom quartile
payback: 32 months
Average
The length of the customer contract should be determined
by the length of the payback period. A single customer
contract should be balanced to return the upfront costs
of building the machine while keeping the subscription cost
manageable. To account for these factors in cost, time and
scale, an important metric is MLV to BOM costs. The
median MLV for all HaaS companies was 7x BOM costs.
The top quartile reached 12x BOM. Things to consider
when evaluating this metric are the value of the data (and
accompanying solutions) and how this value changes over
time. Using another satellite example, as a constellation
is built (many satellites working together), the breadth,
recency and accuracy of the data improves significantly,
and consequently the number of use cases where it is
valuable increases.
Costs beyond the BOM should be factored into the pricing
of the contract, including the cost to sell, deploy, maintain
and recover hardware. The main risk is that a customer will
cancel their service before these costs are recouped.
The best way to mitigate this risk is to ensure that the
market is willing to pay for a machine for the full payback
period. One thing to consider here is the cost of the labor
or the equipment that a HaaS system is offsetting. Take
a security robot for an office building. It must cost less per
month than the guard(s) it would replace. The technology
must also be upgradable. As new use cases emerge, can
the robot add facial recognition and environmental
monitoring or adapt to different terrains? The ease and
ability to add new features is important for maintaining
(or extending) service life. Contract pricing is a critical
element, but so is cost management. The ability to lower
costs is generally key to adoption and ultimately
profitability. As the number of units scale, the cost of
production should fall. Similarly, as installation processes
are refined, costs should consolidate.
Bill of Materials
Evaluation
THE STATE OF HAAS 15
Expected Machine Lifetime Value by BOM Cost1
Cost Breakdown per Unit4
$5K $140K
$810K
$0M
$1M
$2M
$3M
$4M
Sub-$5K $5K-$50K $50K+
BOM Cost Bands
$25k
$0K
$20K
$40K
$60K
$80K
$100K
$120K
$140K
BOM Cost
$5k
$0K
$5K
$10K
$15K
$20K
$25K
$30K
Cost to Sell
$5k
$0K
$5K
$10K
$15K
$20K
$25K
Cost to
Deploy
Middle 50% Companies Median
Middle 50% Companies Median
Expected Machine Lifetime Value to
BOM Ratio2
Operating Profit Margin per HaaS System3
85%
78%
0%
25%
50%
75%
100%
HaaS Companies
The median monthly
cost to run a HaaS
system is 15% of
revenue, resulting in a
median Operating
Profit Margin of
85%.
Middle 50% Companies Median Average
Notes: 1) BOM Cost Per Unit. 2) BOM is the cost to build one HaaS system. 3) Per unit: revenue minus operating expenses divid ed by
revenue. 4) Units are deployable HaaS systems.
Source: SVB State of HaaS Survey results and SVB analysis.
7x
9x
x
2x
4x
6x
8x
10x
12x
14x
HaaS Companies
The median MLV
of a HaaS
Middle 50% Companies Median Average
system is 7x
its cost to make.
$1.5K
$18.0K
$0K
$5K
$10K
$15K
$20K
$25K
$30K
$35K
HaaS Companies
The Russia-Ukraine conflict, COVID-19-induced
factory shutdowns in China and continued global logistics
gridlock have caused supply chains to become stretched.
Navigating these constraints can be a matter of survival
for hardware companies. At the earliest stage, HaaS
companies looking to build a minimum viable product
have more flexibility in sourcing materials. The widespread
availability of OTS parts has made it easier for HaaS
startups to develop prototypes and launch pilots without
developing components in-house. The goal in the early
days is to develop a working product, so startups running
pilots are less focused on BOM costs and more
on meeting pilot milestones. That changes as companies
mature. While early-stage companies can often avoid
logistical bottlenecks because their scale is smaller,
larger companies are tied to their supply chains.
A company building a few dozen machines has more
options in acquiring parts than a company shipping
10,000 units. For this reason, maturing HaaS companies
tend to rigorously engineer their longest lead-time
components to either reduce the lead time or replace
them with a shorter lead-time component.
This trend shows up in the survey data. The average lead
time for a component part is 89 days across all HaaS
companies. However, the longest lead time varies greatly
depending on scale. For HaaS companies with under $100K
in revenue, the average company has to wait four months
for their longest lead-time part. For companies in this
revenue band, this component represented on average 20%
of total BOM cost. Companies with at least $1M in revenue
wait an average of nine months for their longest lead-time
part, which costs just 10% of BOM. The difficulty acquiring
these basic parts is causing an issue for US HaaS
companies to solve. One solution is moving manufacturing
closer to the US by either re- or near-shoring.
Assessing Supply
Chain Efficiency
Notes: 1) Stages based on HaaS revenue: pilot companies have less than $100K, production companies have $100K -$1M, scaled
companies have over $1M. Average HaaS revenue for scaled companies is $41M. 2) Longest lead time component cost divided by BOM.
Source: SVB State of HaaS Survey results and SVB analysis.
THE STATE OF HAAS 16
Lead Time for All Component Parts1Longest Lead Time for a Component Part
Longest Lead-Time Component Cost Longest Lead-Time Component Cost as a
Percent of BOM Cost2
105 120
300
128 154
266
0
60
120
180
240
300
360
Pilot Production Scaled
Days
HaaS Revenue Stage
53
90
75
75
73
114
0
60
120
180
240
300
360
Pilot Production Scaled
Days
HaaS Revenue Stage
Across all HaaS
companies, the
median price of
the longest lead-
time component is
$1,500.
15% 7%
2%
20%
14%
10%
0%
5%
10%
15%
20%
25%
30%
35%
40%
Pilot Production Scaled
% of BOM Cost
HaaS Revenue Stage
Small parts can cause
big delays: The
components requiring
the longest lead time
make up a fraction of the
total BOM cost.
Middle 50% Companies Median
Middle 50% Companies Median
Middle 50% Companies Median
Middle 50% Companies Median Average Average
Average
Average
The market opportunity for HaaS companies is
effectively limitless. Entire industries are up for
disruption as companies create machines to
substitute work that is either monotonous or too
dangerous for human workers. Industries such as
manufacturing, transportation, warehousing and
distribution, food and consumer goods are all prime
for hardware automation. Industrial robots are
performing tasks such as package handling, welding,
and assembly. Increasingly, automated devices are
moving out of the factories and into more public-
facing roles in grocery delivery and healthcare.
Peloton effectively leveraged the HaaS model for
consumers with their subscription model for exercise
hardware and content. Now Apple is considering such
a move for the iPhone.
HaaS companies recognize the sizeable (and
expanding) addressable market for their solutions.
Among survey respondents, the median HaaS
company estimated their total addressable target
market at 10K customers, with the top quartile
stretching to 60K customers. While the benefits of
the HaaS model are clear –reduced capital
expenditure, all-in-one service, scalability, etc., it still
might be a tough sell to companies in industries such
as construction and agriculture, which have
historically been late movers on the technology-
adoption curve. That means HaaS companies must
focus on existing sales opportunities, not aspirational
ones. Maximizing sales per customer is an important
growth strategy for companies looking to meet key
milestones and unlock the market’s potential.
Validating the
Machine’s Market
Notes:1) Estimated number of sites per customer for the HaaS company’s target market. Stages based on HaaS revenue: pilot com panies
have less than $100K, production companies have $100K-$1M, scaled companies have over $1M. Average HaaS revenue for scaled
companies is $41M. 2) Estimated number of HaaS machines deployed per customer site for the HaaS company’s target market.
Source: SVB State of HaaS Survey results and SVB analysis. THE STATE OF HAAS 17
Deployment Sites per Customer by Revenue1Deployment Sites per Customer by BOM Cost
Systems per Customer Site by BOM Cost
7.5 27.5
6
0
20
40
60
80
100
120
140
Sub-$5K $5K-$50K $50K+
BOM Cost Bands
3 3 3
0
5
10
15
20
25
30
Sub-$5K $5K-$50K $50K+
BOM Cost Bands
Systems per Customer Site by Revenue2
73.5 12
0
20
40
60
80
100
120
Pilot Production Scaled
HaaS Revenue Stage
432
0
5
10
15
20
25
30
35
40
Pilot Production Scaled
HaaS Revenue Stage
Middle 50% Companies Median
Middle 50% Companies Median
Middle 50% Companies Median
Middle 50% Companies Median
Preparing for H2 2022 and beyond
Based on our analysis, here are four key findings for HaaS companies to
consider:
SVB Debt Deals for HaaS Companies1
$78M
$54M $40M
$143M
$5.6M $5.9M
$4.9M
$7.8M
2018 2019 2020 2021
3.6x
Total HaaS Debt Committed Average Commitment
Notes: 1) Includes closed debt deals for Hardware companies with recurring revenue models.
Source: SVB proprietary data and SVB analysis.
50+ Loans provided to HaaS companies since 2017
$350M SVB loan capital committed to Haas companies
3.6x Increase in HaaS loan commitments from 2020 to 2021
62% Increase in average HaaS loan size from 2020 to 2021
THE STATE OF HAAS 18
Focus on the Metrics that Matter
SaaS has been eating the digital world for
decades, and HaaS is poised to do the same
for the physical world. To achieve success,
companies need to focus on the metrics that
track the performance of the entire HaaS
system.
Prioritize a Data Strategy
Machines are three-dimensional data
extractors, continually finding new and novel
datasets previously unrecorded. Companies
who best leverage these insights will be well-
positioned to extract incremental value from
their services and establish a moat for the
business.
Reinforce Supply Chains
Global supply chain issues have stunted recent
progress for the hardware industry, increasing
the need for companies to be thoughtful in how
they source inventory. These issues are also
spurring manufacturers to re-shore critical
infrastructure. Any business that can reliably
deliver and maintain its machines has the wind
at its back.
Balance Sources of Capital
Access to capital is paramount for any business.
Scaling a hardware solution consumes
significant upfront capital. Any company
pursuing a HaaS go-to-market strategy must
wisely balance the use of debt and equity capital
to finance deployments.
The recent growth in demand for SVB’s HaaS venture loans offers a useful
gauge on the growing adoption of the HaaS model.
THE STATE OF HAAS 19
Authors
Matthew Trotter
Senior Market Manager
SVB Frontier Tech &
Climate Tech
mtrotter@svb.com
Austin Badger
Managing Director
SVB Frontier Tech
abadger@svb.com
Nick Candy
SVB Director
SVB Market Insights
ncandy@svb.com
Subject Matter Experts Market Insights Team
Josh Pherigo
SVB Senior Researcher
SVB Market Insights
jpherigo@svb.com
Seth Winterroth
Partner
Eclipse Ventures
Seth@eclipse.vc
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